AI Technical Lead

Experience:

12+ Years

Job Type: Full
-Time

As an AI Engineer Lead, you will transform business and financial use cases into deployable AI solutions, driving the design, development, and scaling of production‑grade AI systems. You will mentor and guide engineers while partnering with investment, risk, and compliance teams to deliver robust and innovative AI architectures for financial platforms. This role emphasizes hands‑on technical execution, leadership, and cross‑functional collaboration.

• Translate business, investment, and risk requirements into scalable AI architectures and deployable solutions.
• Design, build, and deploy AI models tailored to project needs, including Cognitive AI (NLP, Computer Vision, Speech, Conversational AI).
• Develop and maintain Document AI and Generative AI models and applications.
• Deliver production‑grade end‑to‑end machine learning solutions, including data preparation, experimentation, model training, serving, and updating.
• Utilize MLOps methodologies to streamline development, deployment, and monitoring of models.
• Optimize and refine algorithms for performance, scalability, and reliability.
• Integrate AI solutions with cloud platforms (AWS, Azure, GCP) and ensure robust CI/CD pipelines (Azure Dev Ops/TFS).
• Ensure the robustness, scalability, and reliability of AI systems in production environments.
• Stay current with the latest advancements in AI, LLMs, MLOps, and machine learning.
• Mentor and provide technical leadership to ML engineers and data scientists on financial AI best practices.
• Lead architecture reviews and drive technical decision‑making for AI systems.
• Partner closely with portfolio managers, quants, risk teams, and compliance officers to deliver AI solutions that meet investment and regulatory requirements.
• Collaborate with cross‑functional teams to integrate AI into financial products and services.

• 12 years of experience in AI/ML, including experience with MLOps, Text Analytics, and Generative AI.
• Strong proficiency in Python and Java; experience with machine learning frameworks (Tensor Flow, PyTorch, Keras, Scikit‑learn).
• Hands‑on experience with cloud platforms (AWS, Azure, GCP).
• Expertise in ML and neural network architectures (Ensemble Models, SVM, CNN, RNN, Transformers).
• Experience with NLP tools (NLTK, Spa Cy, Gensim), MLOps tools (Kubeflow, MLflow, Azure ML), and workflow orchestration (Airflow).
• Familiarity with Microservices architecture; REST API development (FastAPI, Flask, Django).
• Proficiency with SQL and No
  
  SQL databases (Mongo
  
  DB, Postgres, Neo4j).
• Excellent problem‑solving abilities, collaborative mindset, and strong communication skills.

• Bachelor’s, Master’s, or PhD in Statistics, Mathematics, Computer Science, or related quantitative field.
• Experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis.
• Advanced skills in machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks.
• Experience with statistical programming languages (Python, R).
• Published research or contributions to open‑source AI/ML projects.
• Experience visualizing/presenting data (Matplotlib, ggplot).
• Exposure to big data platforms/tools (Hadoop, Spark, Kafka) is a plus.

• Lead the development of cutting‑edge AI solutions for financial systems.
• Opportunity to mentor top engineering talent and collaborate with investment, risk, and compliance teams.
• Dynamic work environment with a focus on technical innovation and professional growth.